[Retracted] EEG‐Based Epileptic Seizure Detection via Machine/Deep Learning Approaches: A Systematic Review

I Ahmad, X Wang, M Zhu, C Wang, Y Pi… - Computational …, 2022 - Wiley Online Library
Epileptic seizure is one of the most chronic neurological diseases that instantaneously
disrupts the lifestyle of affected individuals. Toward develo** novel and efficient …

A review of epileptic seizure detection using machine learning classifiers

MK Siddiqui, R Morales-Menendez, X Huang… - Brain informatics, 2020 - Springer
Epilepsy is a serious chronic neurological disorder, can be detected by analyzing the brain
signals produced by brain neurons. Neurons are connected to each other in a complex way …

A deep learning and grad-CAM based color visualization approach for fast detection of COVID-19 cases using chest X-ray and CT-Scan images

H Panwar, PK Gupta, MK Siddiqui… - Chaos, Solitons & …, 2020 - Elsevier
The world is suffering from an existential global health crisis known as the COVID-19
pandemic. Countries like India, Bangladesh, and other develo** countries are still having …

An overview of machine learning methods in enabling IoMT-based epileptic seizure detection

ALN Al-Hajjar, AKM Al-Qurabat - The Journal of Supercomputing, 2023 - Springer
The healthcare industry is rapidly automating, in large part because of the Internet of Things
(IoT). The sector of the IoT devoted to medical research is sometimes called the Internet of …

Comparison between epileptic seizure prediction and forecasting based on machine learning

G Costa, C Teixeira, MF Pinto - Scientific Reports, 2024 - nature.com
Epilepsy affects around 1% of the population worldwide. Anti-epileptic drugs are an
excellent option for controlling seizure occurrence but do not work for around one-third of …

Evaluation of feature selection methods for classification of epileptic seizure EEG signals

SE Sánchez-Hernández, RA Salido-Ruiz… - Sensors, 2022 - mdpi.com
Epilepsy is a disease that decreases the quality of life of patients; it is also among the most
common neurological diseases. Several studies have approached the classification and …

Machine learning based novel cost-sensitive seizure detection classifier for imbalanced EEG data sets

MK Siddiqui, X Huang, R Morales-Menendez… - International Journal on …, 2020 - Springer
Epilepsy is one of the most prevalent neurological disorders. Its accurate detection is a
challenge since sometimes patients do not experience any prior alert to identify a seizure …

Time domain implementation of pediatric epileptic seizure detection system for enhancing the performance of detection and easy monitoring of pediatric patients

S Chakrabarti, A Swetapadma, A Ranjan… - … Signal Processing and …, 2020 - Elsevier
Objective The clinical phenomenon of epilepsy varies greatly among patients and this in
turn, has its effect on the quality of life they lead. Studies reveal a requisite for efficient …

Detection of Alcoholic EEG signal using LASSO regression with metaheuristics algorithms based LSTM and enhanced artificial neural network classification …

GS Manivannan, K Mani, H Rajaguru, SV Talawar - Scientific Reports, 2024 - nature.com
The world has a higher count of death rates as a result of Alcohol consumption. Identification
is possible because Alcoholic EEG waves have a certain behavior that is totally different …

Automatic detection of epilepsy from EEGs using a temporal convolutional network with a self-attention layer

L Huang, K Zhou, S Chen, Y Chen, J Zhang - BioMedical Engineering …, 2024 - Springer
Background Over 60% of epilepsy patients globally are children, whose early diagnosis and
treatment are critical for their development and can substantially reduce the disease's …